code: def _prepare_text_data(spark):
      df = (
          spark.read.format("csv")
          .option("header", "true")
          .load(
              "wasbs://publicwasb@mmlspark.blob.core.windows.net/text_classification/Emotion_classification.csv"
          )
      )
      indexer = StringIndexer(inputCol="Emotion", outputCol="label")
      indexer_model = indexer.fit(df)
      df = indexer_model.transform(df).drop("Emotion")
  
      train_df, test_df = df.randomSplit([0.85, 0.15], seed=1)
  
      return train_df, test_df
  
file_path: SynapseML/deep-learning/src/test/python/synapsemltest/dl/conftest.py
imports: import os
  import shutil
  import subprocess
  import urllib
  from os.path import join
  import numpy
  import pandas
  import pytest
  import torchvision.transforms
  from pyspark.ml.feature import StringIndexer
label_desc: Use image node_id 4 for calling a global function with example usage: _prepare_text_data(spark) and returns: train_df,  test_df